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''' |
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Taken directly from : https://huggingface.co/spaces/Sagar23p/mistralAI_chatBoat/tree/main |
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''' |
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import streamlit as st |
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from huggingface_hub import InferenceClient |
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import os |
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import sys |
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st.title("ChatGPT-like Chatbot") |
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base_url="https://api-inference.huggingface.co/models/" |
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API_KEY = os.environ.get('HUGGINGFACE_API_KEY') |
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model_links ={ |
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"Mistral-7B":base_url+"mistralai/Mistral-7B-Instruct-v0.2", |
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"Mistral-22B":base_url+"mistral-community/Mixtral-8x22B-v0.1", |
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} |
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model_info ={ |
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"Mistral-7B": |
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{'description':"""The Mistral model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \ |
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\nIt was created by the [**Mistral AI**](https://mistral.ai/news/announcing-mistral-7b/) team as has over **7 billion parameters.** \n""", |
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'logo':'https://mistral.ai/images/logo_hubc88c4ece131b91c7cb753f40e9e1cc5_2589_256x0_resize_q97_h2_lanczos_3.webp'}, |
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"Mistral-22B": |
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{'description':"""The Mistral model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \ |
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\nIt was created by the [**Mistral AI**](https://mistral.ai/news/announcing-mistral-22b/) team as has over **22 billion parameters.** \n""", |
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'logo':'https://mistral.ai/images/logo_hubc88c4ece131b91c7cb753f40e9e1cc5_2589_256x0_resize_q97_h2_lanczos_3.webp'} |
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} |
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def format_promt(message, custom_instructions=None): |
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prompt = "" |
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if custom_instructions: |
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prompt += f"[INST] {custom_instructions} [/INST]" |
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prompt += f"[INST] {message} [/INST]" |
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return prompt |
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def reset_conversation(): |
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''' |
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Resets Conversation |
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''' |
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st.session_state.conversation = [] |
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st.session_state.messages = [] |
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return None |
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models =[key for key in model_links.keys()] |
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selected_model = st.sidebar.selectbox("Select Model", models) |
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temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5)) |
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st.sidebar.button('Reset Chat', on_click=reset_conversation) |
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st.sidebar.write(f"You're now chatting with **{selected_model}**") |
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st.sidebar.markdown(model_info[selected_model]['description']) |
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st.sidebar.image(model_info[selected_model]['logo']) |
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st.sidebar.markdown("*Generated content may be inaccurate or false.*") |
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st.sidebar.markdown("\nLearn how to build this chatbot by original author of this chatbot [here](https://ngebodh.github.io/projects/2024-03-05/).") |
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if "prev_option" not in st.session_state: |
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st.session_state.prev_option = selected_model |
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if st.session_state.prev_option != selected_model: |
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st.session_state.messages = [] |
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st.session_state.prev_option = selected_model |
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reset_conversation() |
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repo_id = model_links[selected_model] |
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st.subheader(f'AI - {selected_model}') |
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if "messages" not in st.session_state: |
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st.session_state.messages = [] |
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for message in st.session_state.messages: |
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with st.chat_message(message["role"]): |
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st.markdown(message["content"]) |
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if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"): |
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custom_instruction = "Act like a Human in conversation" |
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with st.chat_message("user"): |
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st.markdown(prompt) |
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st.session_state.messages.append({"role": "user", "content": prompt}) |
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formated_text = format_promt(prompt, custom_instruction) |
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with st.chat_message("assistant"): |
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client = InferenceClient( |
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model=model_links[selected_model],) |
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output = client.text_generation( |
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formated_text, |
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temperature=temp_values, |
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max_new_tokens=3000, |
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stream=True |
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) |
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response = st.write_stream(output) |
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st.session_state.messages.append({"role": "assistant", "content": response}) |
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